The DailyDialog dataset contains conversation topics of daily life such as ordinary life and financial topics.
It contains bi-turn dialogue flows like Question-Inform and Directive-Commissive dialogue acts.
Thus, the dataset is annotated with those four fundamental dialogue acts to follow unique multi-turn dialogue flow patterns [1]}.
This dataset is manually labelled with six emotion classes and a no_emotion class.
The statistics of the dataset is presented in Table REF , we can see that the no_emotion class dominates the total number of utterances.
However, Happiness dominates within the emotion classes, whereas Fear contains the least number of utterances.
Further, Table REF  also presents the number of utterances for the four dialogue act classes in the dataset for their corresponding emotion classes.
